Data · dataset · 2025
Data-processing methods for D-T source neutron-gamma density logging while drilling
Listed in ScienceDB
With the increasing demand for controllable source logging, research on data-processing algorithms that meet accuracy requirements has become key to the development of controllable-source-logging tools.
Description
This study theoretically derives the relationship between the formation density and inelastic gamma count rate to investigate the data-processing methods for deuterium-tritium (D-T) source neutron-gamma density logging while drilling.
Then, algorithms for the net inelastic gamma count-rate extraction and neutron transport correction are studied using Monte Carlo simulations. A new method for fast-neutron effect identification and additional correction is proposed to improve the density-calculation accuracy of gas-filled and heavy-mineral formations. Finally, the effectiveness and accuracy of the proposed data-processing methods are verified based on simulated and measured data.
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The results show that the density-calculation accuracy of water-bearing conventional formations in simulated data is ±0.02g/cm3. The accuracy of gas-filled and heavy-mineral formations after the additional fast-neutron effect correction is ±0.025g/cm3. For the measured data from the actual tool, the algorithms perform well in the density calculation.
The density results obtained using the processing algorithms are consistent with the density data provided by NeoScope. Therefore, the D-T source neutron-gamma density-logging algorithms proposed can obtain relatively accurate data-processing results for a variety of formations. This study provides technical support for engineering applications and the development of logging tools for controllable-source neutron-density logging.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00186.00580 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Geophysics 70%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00186.00580 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3706 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |